code: def test_mask2former_head_loss(self):
      mask2former_head = Mask2FormerTrackHead(**self.config)
      mask2former_head.init_weights()
      s = 256
      feats = [
          torch.rand(2, 256 * (2**i), s // stride, s // stride)
          for i, stride in enumerate([8, 16, 32, 64])
      ]
      packed_inputs = demo_track_inputs(
          batch_size=1,
          num_frames=2,
          key_frames_inds=[0],
          image_shapes=[(3, s, s)],
          num_classes=2,
          with_mask=True,
      )
      data_sample = packed_inputs["data_samples"][0]
      loss = mask2former_head.loss(feats, [data_sample])
      # loss_cls, loss_mask and loss_dice
      assert len(loss) == 30
  
file_path: mmdetection/tests/test_models/test_tracking_heads/test_mask2former_track_head.py
imports: from unittest import TestCase
  import torch
  from mmengine import Config
  from mmdet.models.tracking_heads import Mask2FormerTrackHead
  from mmdet.structures import DetDataSample, TrackDataSample
  from mmdet.testing import demo_track_inputs
label_desc: Use image node_id 2 for calling the TestMask2FormerHead obj's underlying member method code with example usage: obj.test_mask2former_head_loss() without return types